package com.heima.kafka.sample;

import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.TimeWindows;
import org.apache.kafka.streams.kstream.ValueMapper;

import java.time.Duration;
import java.util.Arrays;
import java.util.Properties;

/**
 * 流式处理 kafka
 */
public class KafkaStreamQuickStart {
    public static void main(String[] args) {
        //kafka的配置中心
        Properties props = new Properties();
        //bootstrap.servers
        props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.86.128:9092");
        props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-quickstart");
        props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        //streams构造器
        StreamsBuilder streamsBuilder = new StreamsBuilder();

        //流式计算
        streamProcessor(streamsBuilder);

        //创建kafkastream对象
        KafkaStreams kafkaStreams = new KafkaStreams(streamsBuilder.build(), props);
        //开启流式计算
        kafkaStreams.start();

    }

    /**
     * 流式计算
     * @param streamsBuilder
     */
    private static void streamProcessor(StreamsBuilder streamsBuilder) {
        //创建kstream对象，同时指定从那个topic中接收消息
        KStream<String,String> stream = streamsBuilder.stream("itcast-topic-input");

        //处理消息的value
        stream.flatMapValues(new ValueMapper<String, Iterable<?>>() {
            @Override
            public Iterable<?> apply(String s) {
                return Arrays.asList(s.split(" "));
            }
        })
                //按照value进行聚合
                .groupBy((key, value) -> value)
                //时间窗口
                .windowedBy(TimeWindows.of(Duration.ofSeconds(10)))
                //统计单词个数
                .count()
                //转换为kStream
                .toStream()
                .map((key,value) ->
                        {
                            System.out.println("key:"+key+",vlaue:"+value);
                            return new KeyValue<>(key.key().toString(),value.toString());
                        })
                //发送消息
                .to("itcast-topic-out");

    }
}
